The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.
Published in |
International Journal of Business and Economics Research (Volume 9, Issue 4)
This article belongs to the Special Issue Microfinance and Local Development |
DOI | 10.11648/j.ijber.20200904.20 |
Page(s) | 234-240 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2020. Published by Science Publishing Group |
Microfinance, DFS, Difficulties, Model, Early Warning
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APA Style
Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. (2020). Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. International Journal of Business and Economics Research, 9(4), 234-240. https://doi.org/10.11648/j.ijber.20200904.20
ACS Style
Maïpa Pakidame; Komivi Ogbone; Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int. J. Bus. Econ. Res. 2020, 9(4), 234-240. doi: 10.11648/j.ijber.20200904.20
AMA Style
Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int J Bus Econ Res. 2020;9(4):234-240. doi: 10.11648/j.ijber.20200904.20
@article{10.11648/j.ijber.20200904.20, author = {Maïpa Pakidame and Komivi Ogbone and Yao Messah Kounetsron}, title = {Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context}, journal = {International Journal of Business and Economics Research}, volume = {9}, number = {4}, pages = {234-240}, doi = {10.11648/j.ijber.20200904.20}, url = {https://doi.org/10.11648/j.ijber.20200904.20}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20200904.20}, abstract = {The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.}, year = {2020} }
TY - JOUR T1 - Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context AU - Maïpa Pakidame AU - Komivi Ogbone AU - Yao Messah Kounetsron Y1 - 2020/07/22 PY - 2020 N1 - https://doi.org/10.11648/j.ijber.20200904.20 DO - 10.11648/j.ijber.20200904.20 T2 - International Journal of Business and Economics Research JF - International Journal of Business and Economics Research JO - International Journal of Business and Economics Research SP - 234 EP - 240 PB - Science Publishing Group SN - 2328-756X UR - https://doi.org/10.11648/j.ijber.20200904.20 AB - The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs. VL - 9 IS - 4 ER -